International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 06 Issue: 09 | Sep 2019
p-ISSN: 2395-0072
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Comparison Review on Autonomous vehicles vs Connected Vehicles
Arun Kumar. N
Mechanical Engineer, Anna University Chennai, Tamil Nadu, India
---------------------------------------------------------------------***---------------------------------------------------------------------Abstract – The automotive industry is expanding its technical
innovations, in which the autonomous cars and connected cars
are two major trends in automotive industry. The development
of autonomous cars and connected cars is a revolution which
will change the perspective of driving comfort and safety of the
passengers. This paper is presented in order to give a
comparison review on autonomous cars vs connected cars.
From the 1960s through the second DARPA Grand Challenge
in 2005, automated vehicle research in the U.S. was primarily
funded by DARPA, the US Army, and the U.S. Navy, yielding
incremental advances in speeds, driving competence in more
complex conditions, controls, and sensor systems.
Companies and research organizations have developed
prototypes.
Key Words: Autonomous car, Connected car, Driverless
vehicle, Connectivity, Self-driving car.
1.2 TECHNICAL CHALLENGES
1. AUTONOMOUS VEHICLES
A self-driving car, also known as an autonomous car,
driverless car, or robotic car, is a vehicle that is capable of
sensing its environment and moving safely with little or no
human input [1]. Self-driving cars combine a variety of
sensors to perceive their surroundings, such as radar, lidar,
sonar, GPS, odometry and inertial measurement units.
Advanced control systems interpret sensory information to
identify appropriate navigation paths, as well as obstacles
and relevant signage [3][4]. Long distance trucks are seen as
being in the forefront of adopting and implementing the
technology.
1.1 HISTORY
Experiments have been conducted on automated driving
systems (ADS) since at least the 1920s, trials began in the
1950s. The first semi-automated car was developed in 1977,
by Japan's Tsukuba Mechanical Engineering Laboratory,
which required specially marked streets that were
interpreted by two cameras on the vehicle and an analog
computer. The vehicle reached speeds up to 30 kilometres
per hour (19 mph) with the support of an elevated rail.
The first truly autonomous cars appeared in the 1980s, with
Carnegie Mellon University's Navlab and ALV [5][6] projects
funded by DARPA starting in 1984 and Mercedes-Benz and
Bundeswehr University Munich's EUREKA Prometheus
Project in 1987.
By 1985, the ALV had demonstrated self-driving speeds on
two lane roads of 31 kilometres per hour (19 mph) with
obstacle avoidance added in 1986 and off-road driving in day
and nighttime conditions by 1987. A major milestone was
achieved in 1995, with CMU's NavLab 5 completing the first
autonomous coast-to-coast drive of the United States. Of the
2,849 miles between Pittsburgh, PA and San Diego, CA, 2,797
miles were autonomous (98.2%), completed with an average
speed of 63.8 miles per hour (102.3 km/h) [7].
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There are different systems that help the self-driving car
control the car. Systems that currently need improvement
include the car navigation system, the location system, the
electronic map, the map matching, the global path planning,
the environment perception, the laser perception, the radar
perception, the visual perception, the vehicle control, the
perception of vehicle speed and direction, the vehicle control
method.
The challenge for driverless car designers is to produce
control systems capable of analyzing sensory data in order to
provide accurate detection of other vehicles and the road
ahead. Modern self-driving cars generally use Bayesian
simultaneous localization and mapping (SLAM) algorithms,
which fuse data from multiple sensors and an off-line map
into current location estimates and map updates [8]. Waymo
has developed a variant of SLAM with detection and tracking
of other moving objects (DATMO), which also handles
obstacles such as cars and pedestrians. Simpler systems may
use roadside real-time locating system (RTLS) technologies
to aid localization. Typical sensors include lidar, stereo
vision, GPS and IMU. Control systems on automated cars may
use Sensor Fusion, which is an approach that integrates
information from a variety of sensors on the car to produce a
more consistent, accurate, and useful view of the
environment.
Researchers at their computer Science and Artificial
Intelligence Laboratory (CSAIL) have developed a new
system, called Map Lite, which allows self-driving cars to
drive on roads that they have never been on before, without
using 3D maps. The system combines the GPS position of the
vehicle, a "sparse topological map" such as OpenStreetMap,
and a series of sensors that observe the road conditions.
Heavy rainfall, hail, or snow could impede the car sensors.
1.3 TESTING
The testing of vehicles with varying degrees of automation
can be carried out either physically, in a closed environment
or, where permitted, on public roads (typically requiring a
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International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 06 Issue: 09 | Sep 2019
p-ISSN: 2395-0072
www.irjet.net
license or permit, or adhering to a specific set of operating
principles), or in a virtual environment, i.e. using computer
simulations. When driven on public roads, automated
vehicles require a person to monitor their proper operation
and "take over" when needed. For example, New York state
has strict requirements for the test driver, such that the
vehicle can be corrected at all times by a licensed operator;
highlighted by Cardian Cube Company's application and
discussions with New York State officials and the NYS DMV.
The progress of automated vehicles can be assessed by
computing the average distance driven between
"disengagements", when the automated system is switched
off, typically by the intervention of a human driver. In 2017,
Waymo reported 63 disengagements over 352,545 miles
(567,366 km) of testing, an average distance of 5,596 miles
(9,006 km) between disengagements, the highest among
companies reporting such figures. Waymo also traveled a
greater total distance than any of the other companies. Their
2017 rate of 0.18 disengagements per 1,000 miles (1,600 km)
was an improvement over the 0.2 disengagements per 1,000
miles (1,600 km) in 2016, and 0.8 in 2015. In March 2017,
Uber reported an average of just 0.67 miles (1.08 km) per
disengagement. In the final three months of 2017, Cruise
(now owned by GM) averaged 5,224 miles (8,407 km) per
disengagement over a total distance of 62,689 miles
(100,888 km) [15]. In July 2018, the first electric driverless
racing car, "Robocar", completed a 1.8-kilometer track, using
its navigation system and artificial intelligence.
1.4 FIELDS OF APPLICATION
In China, Baidu and King Long produce automated minibus, a
vehicle with 14 seats, but without driving seat. With 100
vehicles produced, 2018 will be the first year with
commercial automated service in China. Those minibuses
should be at level 4, that is driverless in closed roads.
1.5 LEVELS OF DRIVING AUTOMATION
In SAE's automation level definitions, "driving mode" means
"a type of driving scenario with characteristic dynamic
driving task requirements [10] (e.g., expressway merging,
high speed cruising, low speed traffic jam, closed-campus
operations, etc.)

Level 0: Automated system issues warnings and may
momentarily intervene but has no sustained vehicle
control.

Level 1 ("hands on"): The driver and the automated
system share control of the vehicle. Examples are
systems where the driver controls steering and the
automated system controls engine power to
maintain a set speed (Cruise Control) or engine and
brake power to maintain and vary speed (Adaptive
Cruise Control or ACC); and Parking Assistance,
where steering is automated while speed is under
manual control. The driver must be ready to retake
full control at any time. Lane Keeping Assistance
(LKA) Type II is a further example of level 1 selfdriving.

Level 2 ("hands off"): The automated system takes
full control of the vehicle (accelerating, braking, and
steering). The driver must monitor the driving and
be prepared to intervene immediately at any time if
the automated system fails to respond properly. The
shorthand "hands off" is not meant to be taken
literally. In fact, contact between hand and wheel is
often mandatory during SAE 2 driving, to confirm
that the driver is ready to intervene.

Level 3 ("eyes off"): The driver can safely turn their
attention away from the driving tasks, e.g. the driver
can text or watch a movie. The vehicle will handle
situations that call for an immediate response, like
emergency braking. The driver must still be
prepared to intervene within some limited time,
specified by the manufacturer, when called upon by
the vehicle to do so.

Level 4 ("mind off"): As level 3, but no driver
attention is ever required for safety, e.g. the driver
may safely go to sleep or leave the driver's seat. Selfdriving is supported only in limited spatial areas
(geofenced) or under special circumstances, like
traffic jams. Outside of these areas or circumstances,
the vehicle must be able to safely abort the trip, e.g.
park the car, if the driver does not retake control.
1.4.1 AUTONOMOUS TRUCKS AND VANS
Many companies (i.e. Otto, Starsky Robotics,) have focused on
autonomous trucks. Automation of trucks is important, not
only due to the improved safety aspects of these very heavy
vehicles, but also due to the ability of fuel savings (through
platooning).
Autonomous vans are being used by online grocers such as
Ocado.
1.4.2 TRANSPORT SYSTEMS
In Europe, cities in Belgium, France, Italy and the UK are
planning to operate transport systems for automated cars,
and Germany, the Netherlands, and Spain have allowed public
testing in traffic. In 2015, the UK launched public trials of the
LUTZ Pathfinder automated pod in Milton Keynes. Beginning
in summer 2015, the French government allowed PSA
Peugeot Citroen to make trials in real conditions in the Paris
area. The experiments were planned to be extended to other
cities such as Bordeaux and Strasbourg by 2016. The alliance
between French companies THALES and Valeo (provider of
the first self-parking car system that equips Audi and
Mercedes premi) is testing its own system. New Zealand is
planning to use automated vehicles for public transport in
Tauranga and Christchurch.
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International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 06 Issue: 09 | Sep 2019
p-ISSN: 2395-0072
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Level 5 ("steering wheel optional"): No human
intervention is required at all. An example would be
a robotic taxi. In the formal SAE definition below,
note in particular what happens in the shift from
SAE 2 to SAE 3: the human driver no longer has to
monitor the environment. This is the final aspect of
the "dynamic driving task" that is now passed over
from the human to the automated system.
2. CONNECTED VEHICLES
A connected car is a car that is equipped with Internet access,
and usually also with a wireless local area network (LAN)
[11]. This allows the car to share internet access, and hence
data, with other devices both inside and outside the vehicle.
For safety-critical applications, it is anticipated that cars will
also be connected using dedicated short-range
communications (DSRC) radios, operating in the FCC granted
5.9 GHz band with very low latency.
2.1 HISTORY
General Motors was the first automaker to bring the first
connected car features to market with OnStar in 1996 in
Cadillac De Ville, Seville and Eldorado. OnStar was created by
GM working with Motorola Automotive (that was later
bought by Continental). The primary purpose was safety and
to get emergency help to a vehicle when there was an
accident. The sooner medical helps arrives the more likely
the drivers and passengers would survive. A cellular
telephone call would be routed to a call center where the
agent sent help.
At first, OnStar only worked with voice but when cellular
systems added data the system was able to send the GPS
location to the call center. After the success of OnStar, many
automakers followed with similar safety programs that
usually come with a free trial for a new car and then a paid
subscription after the trial is over.
Remote diagnostics were introduced in 2001. By 2003
connected car services included vehicle health reports, turnby turn directions and a network access device. Data-only
telematics were first offered in 2007.
In the summer of 2014, Audi was the first automaker to offer
4G LTE Wi-Fi Hotspots access and the first mass deployment
of 4G LTE was by General Motors. By 2015, OnStar had
processed 1 billion requests from customers.
In the UK, the breakdown association 'The AA' introduced the
first piece of connected car technology, in Car Genie that
connects directly to a breakdown service, not only warning of
issues with car health, but intervening directly with a phone
call to customers to help them prevent a breakdown.
In 2017, European technology start-up Stratio Automotive
provides over 10,000 vehicles predictive intelligence
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enabling fleet operators to better manage and maintain their
vehicles.
2.2 TYPES OF CONNECTIVITY
There are 5 ways a vehicle can be connected to its
surroundings and communicate with them [14]:
1. V2I "Vehicle to Infrastructure": The technology captures
data generated by the vehicle and provides information about
the infrastructure to the driver. The V2I technology
communicates information about safety, mobility or
environment related conditions.
2. V2V "Vehicle to Vehicle": The technology communicates
information about speed and position of surrounding vehicles
through a wireless exchange of information. The goal is to
avoid accidents, ease traffic congestions and have a positive
impact on the environment.
3. V2C "Vehicle to Cloud": The technology exchanges
information about and for applications of the vehicle with a
cloud system. This allows the vehicle to use information from
other, though the cloud connected industries like energy,
transportation and smart homes and make use of IoT.
4. V2P "Vehicle to Pedestrian": The technology senses
information about its environment and communicates it to
other vehicles, infrastructure and personal mobile devices.
This enables the vehicle to communicate with pedestrians
and is intended to improve safety and mobility on the road.
5. V2X "Vehicle to Everything": The technology interconnects
all types of vehicles and infrastructure systems with another.
This connectivity includes cars, highways, ships, trains and
airplanes.
2.3 HARDWARE
The necessary hardware can be divided into built-in or
brought-in connection systems. The built-in telematics boxes
most commonly have a proprietary internet connection via a
GSM module and are integrated in the car IT system.
Although most connected cars in the United States use the
GSM operator AT&T with a GSM SIM such as the case with
Volvo [9], some cars such as the Hyundai Blue Link system
utilizes Verizon Wireless Enterprise, a non-GSM CDMA
operator.
Most brought-in devices are plugged in the OBD (on-board
diagnostics) port for electrification and access to vehicle data
and can further be divided into two types of connection:
1.
Hardware relies on customers smartphone for the
internet connection.
2.
Hardware establishes proprietary
connection via GSM module.
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All forms of hardware have typical use cases as drivers. The
built-in solutions were mostly driven by safety regulations in
Europe for an automated Emergency Call. The brought-in
devices usually focus on one customer segment and one
specific use case.
2.4 CATEGORIES OF APPLICATIONS
Applications can be separated into two categories:
1.
2.
Single vehicle applications: In-car content and
service applications implemented by a single vehicle
in connection with a cloud or back office.
Cooperative safety and efficiency applications: they
provide connectivity between vehicles directly have
to work cross-brand and cross-borders and require
standards and regulation.
The connected car segment can be further classified into 8
categories [13].

Mobility management: functions that allow the
driver to reach a destination quickly, safely, and in a
cost-efficient manner (e.g.: Current traffic
information, Parking lot or garage assistance,
Optimized fuel consumption)

Commerce: functions enabling users to purchase
good or services while on-the-go (e.g., fuel, food &
beverage, parking, tolls)

Vehicle management: functions that aid the driver in
reducing operating costs and improving ease of use
(e.g., vehicle condition and service reminders,
remote operation, transfer of usage data)



Breakdown prevention: connected to a breakdown
service, with a back end algorithm predicting
breakdowns and an outbound service intervening
via phone, SMS or push notification.
Safety: functions that warn the driver of external
hazards and internal responses of the vehicle to
hazards (e.g., vehicle condition and service
reminders, remote operation, transfer of usage
data).
Entertainment: functions in the entertainment of
the driver and passengers (e.g., smartphone
interface, WLAN hotspot, music, video, Internet,
social media, mobile office).
information such as a lane closures or obstacles on the road.
By incorporating connected vehicle technology, Autonomous
vehicles will be safer, faster, and more efficient.
Furthermore, virtually all autonomous vehicles will require
some form of connectivity to ensure software and data sets
are current. As autonomous vehicles rely on knowing the
roadway they are traveling on, changes to the roadside such
as new development or construction will require the type of
real-time exchange of information that connected vehicle
technology provides.
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[10]
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[14]
[15]
[16]
3. CONCLUSIONS
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Autonomous vehicles do not need connected vehicle
technology to function since they must be able to
independently navigate the road network. However,
connected vehicle technologies provide valuable information
about the road ahead—allowing rerouting based on new
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